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Recent advances in text-to-image (T2I) diffusion models have significantly improved the quality of generated images. However, providing efficient control over individual subjects, particularly the attributes characterizing them, remains a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Stefan Andreas Baumann , Felix Krause , Michael Neumayr , Nick Stracke , Melvin Sevi , Vincent Tao Hu , Björn Ommer

Despite many attempts to leverage pre-trained text-to-image models (T2I) like Stable Diffusion (SD) for controllable image editing, producing good predictable results remains a challenge. Previous approaches have focused on either…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Sherry X. Chen , Yaron Vaxman , Elad Ben Baruch , David Asulin , Aviad Moreshet , Kuo-Chin Lien , Misha Sra , Pradeep Sen

Recent works on diffusion models have demonstrated a strong capability for conditioning image generation, e.g., text-guided image synthesis. Such success inspires many efforts trying to use large-scale pre-trained diffusion models for…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Zhixing Zhang , Ligong Han , Arnab Ghosh , Dimitris Metaxas , Jian Ren

Large text-to-image models achieved a remarkable leap in the evolution of AI, enabling high-quality and diverse synthesis of images from a given text prompt. However, these models lack the ability to mimic the appearance of subjects in a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-16 Nataniel Ruiz , Yuanzhen Li , Varun Jampani , Yael Pritch , Michael Rubinstein , Kfir Aberman

Text-to-image diffusion models have revolutionized image synthesis and editing, but precise control over stylistic attributes remains a challenge, often causing unintended content modifications. We propose an approach for fine-grained…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Max Reimann , Benito Buchheim , Jürgen Döllner

Facial video editing has become increasingly important for content creators, enabling the manipulation of facial expressions and attributes. However, existing models encounter challenges such as poor editing quality, high computational…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Tharun Anand , Aryan Garg , Kaushik Mitra

With the great success of text-conditioned diffusion models in creative text-to-image generation, various text-driven image editing approaches have attracted the attentions of many researchers. However, previous works mainly focus on…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Zhiyuan Ma , Guoli Jia , Bowen Zhou

Face editing modifies the appearance of face, which plays a key role in customization and enhancement of personal images. Although much work have achieved remarkable success in text-driven face editing, they still face significant…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Xin Zhang , Siting Huang , Xiangyang Luo , Yifan Xie , Weijiang Yu , Heng Chang , Fei Ma , Fei Yu

Large-scale Text-to-Image (T2I) diffusion models demonstrate significant generation capabilities based on textual prompts. Based on the T2I diffusion models, text-guided image editing research aims to empower users to manipulate generated…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Chuanming Tang , Kai Wang , Fei Yang , Joost van de Weijer

Recent advances in diffusion models enable many powerful instruments for image editing. One of these instruments is text-driven image manipulations: editing semantic attributes of an image according to the provided text description. %…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Nikita Starodubcev , Dmitry Baranchuk , Valentin Khrulkov , Artem Babenko

Text-guided image-to-image diffusion models excel in translating images based on textual prompts, allowing for precise and creative visual modifications. However, such a powerful technique can be misused for spreading misinformation,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Wenhao Wang , Yifan Sun , Zongxin Yang , Zhentao Tan , Zhengdong Hu , Yi Yang

Diffusion models (DMs) can generate realistic images with text guidance using large-scale datasets. However, they demonstrate limited controllability in the output space of the generated images. We propose a novel learning method for…

Computer Vision and Pattern Recognition · Computer Science 2023-05-11 Rumeysa Bodur , Erhan Gundogdu , Binod Bhattarai , Tae-Kyun Kim , Michael Donoser , Loris Bazzani

Diffusion models have exhibited impressive prowess in the text-to-image task. Recent methods add image-level structure controls, e.g., edge and depth maps, to manipulate the generation process together with text prompts to obtain desired…

Computer Vision and Pattern Recognition · Computer Science 2024-08-23 Yibo Zhao , Liang Peng , Yang Yang , Zekai Luo , Hengjia Li , Yao Chen , Zheng Yang , Xiaofei He , Wei Zhao , qinglin lu , Boxi Wu , Wei Liu

Despite the ability of existing large-scale text-to-image (T2I) models to generate high-quality images from detailed textual descriptions, they often lack the ability to precisely edit the generated or real images. In this paper, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Chong Mou , Xintao Wang , Jiechong Song , Ying Shan , Jian Zhang

Text-conditioned diffusion models can generate impressive images, but fall short when it comes to fine-grained control. Unlike direct-editing tools like Photoshop, text conditioned models require the artist to perform "prompt engineering,"…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Michelle Shu , Charles Herrmann , Richard Strong Bowen , Forrester Cole , Ramin Zabih

A significant research effort is focused on exploiting the amazing capacities of pretrained diffusion models for the editing of images.They either finetune the model, or invert the image in the latent space of the pretrained model. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Senmao Li , Joost van de Weijer , Taihang Hu , Fahad Shahbaz Khan , Qibin Hou , Yaxing Wang , Jian Yang , Ming-Ming Cheng

Diffusion models have made significant advances in text-guided synthesis tasks. However, editing user-provided images remains challenging, as the high dimensional noise input space of diffusion models is not naturally suited for image…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Jiteng Mu , Michaël Gharbi , Richard Zhang , Eli Shechtman , Nuno Vasconcelos , Xiaolong Wang , Taesung Park

Research in vision-language models has seen rapid developments off-late, enabling natural language-based interfaces for image generation and manipulation. Many existing text guided manipulation techniques are restricted to specific classes…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Paramanand Chandramouli , Kanchana Vaishnavi Gandikota

Large-scale Text-to-Image (T2I) diffusion models have revolutionized image generation over the last few years. Although owning diverse and high-quality generation capabilities, translating these abilities to fine-grained image editing…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Chong Mou , Xintao Wang , Jiechong Song , Ying Shan , Jian Zhang

Text-guided image editing can have a transformative impact in supporting creative applications. A key challenge is to generate edits that are faithful to input text prompts, while consistent with input images. We present Imagen Editor, a…